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This paper is in the following e-collection/theme issue:

Frailty Detection, Assessment and Prediction (210) New Methods (1713) Longitudinal and Cohort Studies in Public Health (876) Machine Learning (2976) Postoperative Rehabilitation (91) Falls Prevention in the Elderly (192) Postoperative Monitoring and Telemonitoring (235) Epidemiologic Studies and Surveys in Elder Care (157) Aging with Chronic Disease (500) Artificial Intelligence (4434) AI in Older Adult Care (198) Outcomes Research in Perioperative Medicine (70)

Published on in Vol 9 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/90705, first published .
Elderly woman using a walker with a caregiver's assistance in a rehabilitation center.

Predicting Frailty Trajectories Using Interpretable Machine Learning Among Older Adults Following Hip Surgery: Prospective Longitudinal Study

Predicting Frailty Trajectories Using Interpretable Machine Learning Among Older Adults Following Hip Surgery: Prospective Longitudinal Study

Authors of this article:

Jingying Huang1 Author Orcid Image ;   Qinqin Fan2 Author Orcid Image ;   Huiqin Shi3 Author Orcid Image ;   Jiaojiao Chen1 Author Orcid Image ;   Hongbo Gao2 Author Orcid Image ;   Kailai Gu3 Author Orcid Image ;   Jin Yang1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jingying Huang   1 , MSN ;   Qinqin Fan   2 , PhD ;   Huiqin Shi   3 , BSN ;   Jiaojiao Chen   1 , MSN ;   Hongbo Gao   2 , BSc ;   Kailai Gu   3 , BSN ;   Jin Yang   1 , MSN

1 Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, China

2 Shanghai Maritime University, Shanghai, China

3 Zhejiang Chinese Medical University, Hangzhou, China

Corresponding Author:

  • Jingying Huang, MSN
  • Sir Run Run Shaw Hospital
  • No. 3, Qingchun East Road
  • Hangzhou, Zhejiang
  • China
  • Phone: 86 17757173794
  • Email: h.j.y@163.com